mia-0032

<?php

class ImageResizer {

	public function resize($path, $width, $height) {
		if (is_int($width) === FALSE || is_int($height) === FALSE) {
			throw new Exception('$widthまたは$heightが不正');
		}
		if (is_string($path) && is_file($path)) {
			$this->resizeImage($path, $width, $height);

mia-0032

using System;
using System.Collections.Generic;
using System.ComponentModel;
using System.Data;
using System.Drawing;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using System.Windows.Forms;

mia-0032

package controllers;

import play.mvc.*;
import views.html.*;

public class HelloWorld extends Controller {
    public static Result index() {
        return ok("<b>Hello World</b>").as("text/html");
    }

mia-0032

<?xml version="1.0" encoding="utf-8"?>
<s:WindowedApplication xmlns:fx="http://ns.adobe.com/mxml/2009" 
    				   xmlns:s="library://ns.adobe.com/flex/spark" 
					   xmlns:mx="library://ns.adobe.com/flex/mx">
<s:Button label="Hello World!!" click="clickButton()" />
<fx:Script>
	import mx.controls.Alert;
	
	public function clickButton():Boolean {
		Alert.show("Hello World!!");

mia-0032

package
{
    import flash.display.Sprite;
	import flash.text.TextField;
	import flash.text.TextFieldAutoSize;
	import flash.text.TextFormat;
	
	public class HelloworldAs extends Sprite
	{
		public function HelloworldAs()

mia-0032

package Innocencer.DisplayEffect
{
    public class Circle extends EffectBase
	{
		public function Circle(x:Number, y:Number)
		{
			super(x, y);
		}

		public override function display():void

mia-0032

# -*- coding:utf-8 -*-

import numpy
from scipy import stats

n = 200
#正規分布にあてはまる乱数を生成
score_x = numpy.random.normal(171.77, 5.54, n)
score_y = numpy.random.normal(62.49, 7.89, n)

mia-0032

data = read.table('result.txt', header=TRUE, sep="\t", fileEncoding="utf8")
summary(data)

data$www = log(data$www + 1)
data$gj = log(data$gj + 1)

plot.new()
plot(data$www, data$gj, xlim=c(0, 12), ylim=c(0, 12), xlab="log(www_count)",ylab="log(gj_count)")

#線形回帰してみる

mia-0032

# -*- coding:utf-8 -*-

import numpy
import pylab

#データの生成
n = 200
score_x = numpy.random.normal(171.77, 5.54, n)
score_y = numpy.random.normal(62.49, 7.89, n)

mia-0032

# -*- coding:utf-8 -*-

import numpy
import pylab
#import statsmodels.api

from sklearn import linear_model

n = 200
#データの生成